Lazy methods have become key to modern methods of working with persistent Jordan bases, since \(E\)  has a tremendous number of nonzero entries, in general.
The archetypal example of a lazy method in this field is the computational technique introduced in [1]}, which does not store the rows of a reduced matrix in memory, but rather re-constructs them each time they are needed.
At the cost of extra computation, such lazy methods circumvent some of the most challenging problems in computation for TDA, such as sparse matrices that are too large to store in memory.
